Nicolas Christianson is an assistant research professor in the Department of Computer Science, a member of the Data Science and AI Institute, and an associate member of the Ralph O’Connor Sustainable Energy Institute at the Johns Hopkins University.
His research lies broadly at the intersection of algorithms, machine learning, and optimization, with a focus on developing new, theoretically grounded algorithms and AI/ML frameworks for reliable decision-making under uncertainty. Christianson’s work spans theory and practice, and he is particularly interested in online and learning-augmented algorithms, uncertainty quantification, ML for optimization, and applications in robust, efficient, and sustainable energy and computing systems.
He has published research at top conferences, including the International Conference on Machine Learning, the Conference on Learning Theory, ACM SIGMETRICS, and the ACM International Conference on Future and Sustainable Energy Systems. Christianson’s work has been recognized with distinctions such as a Stanford Energy Postdoctoral Fellowship, an NSF Graduate Research Fellowship, a PIMCO Data Science Fellowship, and the California Institute of Technology’s Ben P.C. Chou Doctoral Prize in Information Science and Technology and Demetriades-Tsafka-Kokkalis Prize in Environmentally Benign Renewable Energy Sources.
Christianson received his PhD in computing and mathematical sciences from Caltech in 2025 and an AB in applied mathematics from Harvard University in 2020. He will be spending a year as a postdoctoral fellow at Stanford before joining Johns Hopkins as an assistant professor in Fall 2026.